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Development and validation of a LASSO-Based FDG PET/CT model for predicting colorectal adenoma in asymptomatic individuals undergoing colonoscopy

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dc.contributor.authorKang, Jeonghyun-
dc.contributor.authorKim, Youngmin-
dc.contributor.authorJeong, Yeongbeom-
dc.contributor.authorLee, Hye Sun-
dc.contributor.authorRyu, Young Hoon-
dc.contributor.authorJeon, Tae Joo-
dc.contributor.authorLee, Jae-Hoon-
dc.date.accessioned2026-01-16T05:18:29Z-
dc.date.available2026-01-16T05:18:29Z-
dc.date.created2025-12-11-
dc.date.issued2025-11-
dc.identifier.issn0914-7187-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/209789-
dc.description.abstractObjectiveColonoscopy is the gold standard for colorectal cancer (CRC) screening; however, its invasiveness, cost, and associated risks limit its use in population-wide programs. Therefore, effective noninvasive tools for identifying individuals at high risk for colorectal adenomas-the precursors to CRC-are needed. 2-deoxy-2-[F-1(8)] fluoro-D-glucose positron emission tomography/computed tomography (FDG PET/CT) captures systemic metabolic and inflammatory activity and may offer imaging biomarkers for adenoma risk stratification.MethodsWe retrospectively analyzed 754 asymptomatic individuals who underwent both colonoscopy and FDG PET/CT within 30 days as part of health screening. PET/CT-derived variables included standardized uptake values (SUVs) from visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), skeletal muscle, liver, spleen, bone marrow, and colorectal wall. Clinical data included age, sex, and body mass index (BMI). A least absolute shrinkage and selection operator (LASSO) logistic regression model was trained on 452 individuals and tested in a separate validation cohort of 302.ResultsThe final LASSO model selected eight variables, including VAT area (positive association) and multiple tissue-specific SUV features (negative associations). In the test set, the model achieved an area under the curve (AUC) of 0.693 (95% confidence interval: 0.631-0.754), significantly outperforming individual predictors such as VAT area (AUC = 0.630, P = 0.011), VAT HU (AUC = 0.585, P = 0.001), and SAT SUVmax (AUC = 0.616, P = 0.046). Decision curve analysis demonstrated superior net clinical benefit compared to univariable models.ConclusionA multivariable model integrating FDG PET/CT-derived metabolic features with clinical parameters enables noninvasive prediction of colorectal adenomas. This imaging-based approach may help identify individuals most likely to benefit from colonoscopy, potentially improving the efficiency of CRC screening strategies in opportunistic or high-risk settings.-
dc.languageEnglish-
dc.publisherSpringer Japan-
dc.relation.isPartOfANNALS OF NUCLEAR MEDICINE-
dc.relation.isPartOfANNALS OF NUCLEAR MEDICINE-
dc.titleDevelopment and validation of a LASSO-Based FDG PET/CT model for predicting colorectal adenoma in asymptomatic individuals undergoing colonoscopy-
dc.typeArticle-
dc.contributor.googleauthorKang, Jeonghyun-
dc.contributor.googleauthorKim, Youngmin-
dc.contributor.googleauthorJeong, Yeongbeom-
dc.contributor.googleauthorLee, Hye Sun-
dc.contributor.googleauthorRyu, Young Hoon-
dc.contributor.googleauthorJeon, Tae Joo-
dc.contributor.googleauthorLee, Jae-Hoon-
dc.identifier.doi10.1007/s12149-025-02122-8-
dc.relation.journalcodeJ00167-
dc.identifier.eissn1864-6433-
dc.identifier.pmid41212374-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s12149-025-02122-8-
dc.subject.keywordFDG PET/CT-
dc.subject.keywordColorectal adenoma-
dc.subject.keywordLASSO-
dc.subject.keywordColonoscopy-
dc.subject.keywordRisk stratification-
dc.contributor.affiliatedAuthorKang, Jeonghyun-
dc.contributor.affiliatedAuthorKim, Youngmin-
dc.contributor.affiliatedAuthorJeong, Yeongbeom-
dc.contributor.affiliatedAuthorLee, Hye Sun-
dc.contributor.affiliatedAuthorRyu, Young Hoon-
dc.contributor.affiliatedAuthorJeon, Tae Joo-
dc.contributor.affiliatedAuthorLee, Jae-Hoon-
dc.identifier.scopusid2-s2.0-105021451456-
dc.identifier.wosid001610506600001-
dc.identifier.bibliographicCitationANNALS OF NUCLEAR MEDICINE, 2025-11-
dc.identifier.rimsid90269-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorFDG PET/CT-
dc.subject.keywordAuthorColorectal adenoma-
dc.subject.keywordAuthorLASSO-
dc.subject.keywordAuthorColonoscopy-
dc.subject.keywordAuthorRisk stratification-
dc.subject.keywordPlusSTANDARDIZED UPTAKE VALUE-
dc.subject.keywordPlusCANCER-
dc.subject.keywordPlusINFLAMMATION-
dc.subject.keywordPlusGUIDELINES-
dc.subject.keywordPlusOBESITY-
dc.subject.keywordPlusRISK-
dc.type.docTypeArticle; Early Access-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryRadiology, Nuclear Medicine & Medical Imaging-
dc.relation.journalResearchAreaRadiology, Nuclear Medicine & Medical Imaging-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers

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